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Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}},"outputId":"3aa96e5b-a5c1-4899-887d-eae98e08f6d7"},"source":["!pip install SentencePiece\n","!pip install transformers"],"execution_count":2,"outputs":[{"output_type":"stream","text":["Collecting SentencePiece\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/f5/99/e0808cb947ba10f575839c43e8fafc9cc44e4a7a2c8f79c60db48220a577/sentencepiece-0.1.95-cp37-cp37m-manylinux2014_x86_64.whl (1.2MB)\n","\u001b[K     |████████████████████████████████| 1.2MB 5.2MB/s \n","\u001b[?25hInstalling collected packages: SentencePiece\n","Successfully installed SentencePiece-0.1.95\n","Collecting transformers\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/d8/b2/57495b5309f09fa501866e225c84532d1fd89536ea62406b2181933fb418/transformers-4.5.1-py3-none-any.whl (2.1MB)\n","\u001b[K     |████████████████████████████████| 2.1MB 5.6MB/s \n","\u001b[?25hCollecting tokenizers<0.11,>=0.10.1\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/ae/04/5b870f26a858552025a62f1649c20d29d2672c02ff3c3fb4c688ca46467a/tokenizers-0.10.2-cp37-cp37m-manylinux2010_x86_64.whl (3.3MB)\n","\u001b[K     |████████████████████████████████| 3.3MB 51.5MB/s \n","\u001b[?25hRequirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.7/dist-packages (from transformers) (2019.12.20)\n","Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from transformers) (2.23.0)\n","Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.7/dist-packages (from transformers) (4.41.1)\n","Requirement already satisfied: importlib-metadata; python_version < \"3.8\" in /usr/local/lib/python3.7/dist-packages (from transformers) (3.10.1)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.7/dist-packages (from transformers) (3.0.12)\n","Requirement already satisfied: packaging in /usr/local/lib/python3.7/dist-packages (from transformers) (20.9)\n","Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.7/dist-packages (from transformers) (1.19.5)\n","Collecting sacremoses\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/75/ee/67241dc87f266093c533a2d4d3d69438e57d7a90abb216fa076e7d475d4a/sacremoses-0.0.45-py3-none-any.whl (895kB)\n","\u001b[K     |████████████████████████████████| 901kB 56.5MB/s \n","\u001b[?25hRequirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (2020.12.5)\n","Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (3.0.4)\n","Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (2.10)\n","Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (1.24.3)\n","Requirement already satisfied: typing-extensions>=3.6.4; python_version < \"3.8\" in /usr/local/lib/python3.7/dist-packages (from importlib-metadata; python_version < \"3.8\"->transformers) (3.7.4.3)\n","Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata; python_version < \"3.8\"->transformers) (3.4.1)\n","Requirement already satisfied: pyparsing>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging->transformers) (2.4.7)\n","Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers) (1.15.0)\n","Requirement already satisfied: click in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers) (7.1.2)\n","Requirement already satisfied: joblib in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers) (1.0.1)\n","Installing collected packages: tokenizers, sacremoses, transformers\n","Successfully installed sacremoses-0.0.45 tokenizers-0.10.2 transformers-4.5.1\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"r0hS6VtbiFgz","executionInfo":{"status":"ok","timestamp":1618945215438,"user_tz":-180,"elapsed":934,"user":{"displayName":"Savas Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}}},"source":["import pandas as pd"],"execution_count":3,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"AjQTF9MPh7k9","executionInfo":{"status":"ok","timestamp":1618945220894,"user_tz":-180,"elapsed":4981,"user":{"displayName":"Savas Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}},"outputId":"07d4ba30-4e0e-4fe8-8ea6-e1e31843547d"},"source":["#BERT-BASE (L=12, H=768, A=12, Total Parameters=110M) \n","from transformers import BertConfig, BertModel\n","bert_base= BertConfig()\n","model = BertModel(bert_base)\n","print(f\"{model.num_parameters() /(10**6)} million parameters\")"],"execution_count":4,"outputs":[{"output_type":"stream","text":["109.48224 million parameters\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"ryna0jJth7k_"},"source":[""],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"11vJBKiA2SDk","executionInfo":{"status":"ok","timestamp":1618945228349,"user_tz":-180,"elapsed":1032,"user":{"displayName":"Savas Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}},"outputId":"18e019b9-207b-4ee5-b345-0c9ac11e711f"},"source":["# Albert-base Configuration\n","from transformers import AlbertConfig, AlbertModel\n","albert_base = AlbertConfig(\n","     hidden_size=768,\n","     num_attention_heads=12,\n","     intermediate_size=3072,\n"," )\n","model = AlbertModel(albert_base)\n","print(f\"{model.num_parameters() /(10**6)} million parameters\")"],"execution_count":5,"outputs":[{"output_type":"stream","text":["11.683584 million parameters\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"dn-u5JU17iFp"},"source":["# Table from the original ALBERT paper \n","from IPython.display import Image \n","albert = Image(filename='albert.png')\n","\n","display(albert)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Fvg3X4_ch7lB","executionInfo":{"status":"ok","timestamp":1618945241272,"user_tz":-180,"elapsed":6107,"user":{"displayName":"Savas Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}},"outputId":"dc2fe06e-a2d8-4be7-de10-0789b93ddca1"},"source":["#BERT-LARGE (L=24, H=1024, A=16, Total Parameters=340M).\n","from transformers import BertConfig, BertModel\n","bert_large= BertConfig(hidden_size=1024, \n","                      num_hidden_layers=24 ,\n","          num_attention_heads=16,\n","          intermediate_size=4096\n","     )\n","model = BertModel(bert_large)\n","print(f\"{model.num_parameters() /(10**6)} million parameters\")\n"],"execution_count":7,"outputs":[{"output_type":"stream","text":["335.141888 million parameters\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"J1_k9flYh7lB","executionInfo":{"status":"ok","timestamp":1618945246489,"user_tz":-180,"elapsed":4505,"user":{"displayName":"Savas Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}},"outputId":"ebe537a9-5599-485e-e68d-af3774f0fb8a"},"source":["# ALBERT-xxlarge configuration  by default\n","from transformers import AlbertConfig, AlbertModel\n","albert_xxlarge= AlbertConfig()\n","model = AlbertModel(albert_xxlarge)\n","print(f\"{model.num_parameters() /(10**6)} million parameters\")"],"execution_count":8,"outputs":[{"output_type":"stream","text":["222.595584 million parameters\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"bJ4J8m-V2SyX"},"source":["# how to use Albert model"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"Z8lb4E3V7qtt","executionInfo":{"status":"ok","timestamp":1618945373476,"user_tz":-180,"elapsed":6052,"user":{"displayName":"Savas Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}}},"source":["from transformers import AlbertTokenizer, AlbertModel\n","tokenizer = AlbertTokenizer.from_pretrained('albert-large-v2')\n","model = AlbertModel.from_pretrained(\"albert-large-v2\")\n","text = \"The cat is so sad .\"\n","encoded_input = tokenizer(text, return_tensors='pt')\n","output = model(**encoded_input)"],"execution_count":11,"outputs":[]},{"cell_type":"code","metadata":{"id":"ElLzLpmfh7lD"},"source":[""],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"7z1XFNPah7lD"},"source":["You can use output object or use the model directly with a pipeline for masked language modeling:"]},{"cell_type":"markdown","metadata":{"id":"2wMSKaguh7lE"},"source":[""]},{"cell_type":"code","metadata":{"id":"tpNyd8037jLl","colab":{"base_uri":"https://localhost:8080/","height":398,"referenced_widgets":["8b81b202454a40d59e8e8a22fdf627c0","e9d4cadaeb894944a8db0ea909e93196","7811277a0cdb44938fe505256f255efe","e19e416b873a44ed808a9af58a466974","82aab4542ef042458b6f3cb5ac0c337b","2852b37749014cb980a7ecb6ae74c868","d7b76df2db344d11859f8b080107f453","84a9d55078224dc2a97f11dfc90c46d8","fb0368271bea4e3cb04d944ab561e64e","9e8becbd17ce4edabe793108899651dc","638e0c276d3143a29d5b4d42ea13746b","b4157696ed5948c49910a08a93762ddc","25cf99fba6174c52bf25208305478283","8683bdd7ed704c0a8f6e99aad5304230","f25b9869dbe441e6b358b96c3c245eed","d04cbdd73492412ca88c6b2feec7e3e1","56c27674eeb04d6ab7b8c1e162315908","7f6c16ba09134896a9c44e03641ba4e0","5b3ca08719b440f38d3e91952ad3c541","65a7480c17a04c70b6b80f386bdd2279","641baab0aff04da29b836ea901e1b797","51b706dd85d543f9bed483c713a62bb8","17a33b95eb3247bc97756dd1bebf597a","70dffa0666b74cbc9cc0cbb55fbf9a6d","f96649fb338f43089959752262256234","3fa4f64db4cb4ba691bec79675d95110","2b2ee1a36c954aa49bde80ba21b8d0f4","edf455a918d14c8b8c574fdf41f1754d","f49667bc9cde43c7a914a223ea1009d3","ab371af6b3f146d8ba0c859aff8a5cba","d2a0dc04f9b74618b485dbfe0b7cb3bc","1a73ffbaaba34625b7091e2d268b856e"]},"executionInfo":{"status":"ok","timestamp":1618945470704,"user_tz":-180,"elapsed":14643,"user":{"displayName":"Savas Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}},"outputId":"fc66db3d-ab58-48da-8a53-9e0ab35f7a64"},"source":["from transformers import pipeline\n","fillmask = pipeline('fill-mask', model='albert-base-v2')\n","pd.DataFrame(fillmask(\"The cat is so [MASK] .\"))"],"execution_count":12,"outputs":[{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"8b81b202454a40d59e8e8a22fdf627c0","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=684.0, style=ProgressStyle(description_…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"fb0368271bea4e3cb04d944ab561e64e","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=47376696.0, style=ProgressStyle(descrip…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"56c27674eeb04d6ab7b8c1e162315908","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=760289.0, style=ProgressStyle(descripti…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"f96649fb338f43089959752262256234","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=1312669.0, style=ProgressStyle(descript…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>sequence</th>\n","      <th>score</th>\n","      <th>token</th>\n","      <th>token_str</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>the cat is so cute.</td>\n","      <td>0.281028</td>\n","      <td>10901</td>\n","      <td>cute</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>the cat is so adorable.</td>\n","      <td>0.094894</td>\n","      <td>26354</td>\n","      <td>adorable</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>the cat is so happy.</td>\n","      <td>0.042963</td>\n","      <td>1700</td>\n","      <td>happy</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>the cat is so funny.</td>\n","      <td>0.040976</td>\n","      <td>5066</td>\n","      <td>funny</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>the cat is so affectionate.</td>\n","      <td>0.024234</td>\n","      <td>28803</td>\n","      <td>affectionate</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                      sequence     score  token     token_str\n","0          the cat is so cute.  0.281028  10901          cute\n","1      the cat is so adorable.  0.094894  26354      adorable\n","2         the cat is so happy.  0.042963   1700         happy\n","3         the cat is so funny.  0.040976   5066         funny\n","4  the cat is so affectionate.  0.024234  28803  affectionate"]},"metadata":{"tags":[]},"execution_count":12}]},{"cell_type":"code","metadata":{"id":"WbJ5F8iy7jx1","executionInfo":{"status":"ok","timestamp":1618945481296,"user_tz":-180,"elapsed":1103,"user":{"displayName":"Savas Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}}},"source":[""],"execution_count":12,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"ZVcK5G8jh7lF"},"source":["ROBERTA"]},{"cell_type":"code","metadata":{"id":"T4GzKxvlh7lF","colab":{"base_uri":"https://localhost:8080/","height":268,"referenced_widgets":["465333225c02447caeec9b9a571e5983","a57f026c1a0f464bb268c28814b8de83","01963ecdee5c40a388bfb35fe628a619","ed3875f6692b44e5b1ffd0e1ca7af53e","46f8fc90798c4b8a94611ffa82c9db60","d6713566083c4c7f953f9425a8b28bb5","1451a7dcdb6e4d6e9f405a97aef33a45","9f455b91ff7c43cfa203359112fce1b4","f72d6ca6d5184231a4fa2cd5c6351c1e","997ad1f8bc314985806e548deb8c1ae7","bdf522daca0b46ab93cbd65d29ad0162","a6f8b379a1ac4105b8662b5bd630b7db","ff00e27046a045ea924ff1754474c7eb","626962251d7c4eafa98f8f242968fa1c","6ed5b756b62a4d609db39aa4ab2f8082","1b9a4d222d55472f8b1480660c7e02b3","ec1345d2103b4bc9a6ffccc76e563775","f7924d2423b7439ba8f9ad53b5e80103","789ff7bb65504f348724e82694195c8a","884b11b5065b41cb9afe9fd1fe5e6e1d","553defecedd4434b9430c2df5d980892","0ef2c7fbe35c43db987f798e9cd6cd8c","1834e18669d04ff89429f35cda3c6239","e508b09580164517b1eabe2cde414400","cbe9234d51a34833a0f918d6b32f8639","3765208b7d144da2adbec92f63f7b276","8e2551afb40b42a6b8c0b9c20893863a","31a02239eb144ccbba92af6d8e711865","b09e2470cf1148bcab393d8c0225090d","5080277d9dbb4c84921244183689f380","2b39eae352904443aea68ddda360e46b","98e03690789349a0a728289ee028fab7","39e873f8fc0c4c9ca04a63b7ee162123","2082348ed20e445092c4ce01e4bd6d9b","2679c570ab1f4252896303ef215e7aef","28bc16669c04494ab3a7389c25f6206d","f0805f7a9fb54f65802f776f9ac67dc8","d9287556dab7471c90bf16ff3187a806","7282bc2a3c754085915068fa40d018b0","dc8804200b0940eb861c29e8ae42c626"]},"executionInfo":{"status":"ok","timestamp":1618945533564,"user_tz":-180,"elapsed":22519,"user":{"displayName":"Savas Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}},"outputId":"8b08a445-d524-4830-9b5b-d31a5c081c14"},"source":["from transformers import RobertaTokenizer, RobertaModel\n","tokenizer = RobertaTokenizer.from_pretrained('roberta-base')\n","model = RobertaModel.from_pretrained('roberta-base')\n","text = \"The cat is so sad .\"\n","encoded_input = tokenizer(text, return_tensors='pt')\n","output = model(**encoded_input)"],"execution_count":13,"outputs":[{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"465333225c02447caeec9b9a571e5983","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=898823.0, style=ProgressStyle(descripti…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"f72d6ca6d5184231a4fa2cd5c6351c1e","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=456318.0, style=ProgressStyle(descripti…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"ec1345d2103b4bc9a6ffccc76e563775","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=1355863.0, style=ProgressStyle(descript…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"cbe9234d51a34833a0f918d6b32f8639","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=481.0, style=ProgressStyle(description_…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"39e873f8fc0c4c9ca04a63b7ee162123","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=501200538.0, style=ProgressStyle(descri…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"JCUUVQ1Uh7lG","executionInfo":{"status":"ok","timestamp":1618945538230,"user_tz":-180,"elapsed":1179,"user":{"displayName":"Savas Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}}},"source":[""],"execution_count":13,"outputs":[]},{"cell_type":"code","metadata":{"id":"Rs9cAxjqh7lG","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1618945540266,"user_tz":-180,"elapsed":2787,"user":{"displayName":"Savas Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}},"outputId":"e7320720-2da0-4db8-8532-eb584859c737"},"source":["from transformers import RobertaConfig, RobertaModel\n","conf= RobertaConfig()\n","model = RobertaModel(conf)\n","print(f\"{model.num_parameters() /(10**6)} million parameters\")"],"execution_count":14,"outputs":[{"output_type":"stream","text":["109.48224 million parameters\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"WaZ8RWZVh7lG","executionInfo":{"status":"ok","timestamp":1618945542206,"user_tz":-180,"elapsed":825,"user":{"displayName":"Savas Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}}},"source":[""],"execution_count":14,"outputs":[]},{"cell_type":"code","metadata":{"id":"4w92uHeHh7lH","colab":{"base_uri":"https://localhost:8080/","height":198},"executionInfo":{"status":"ok","timestamp":1618945554703,"user_tz":-180,"elapsed":11750,"user":{"displayName":"Savas Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}},"outputId":"7f3a39fe-03be-4113-9779-0b40be7af88d"},"source":["from transformers import pipeline\n","fillmask = pipeline('fill-mask', model=\"roberta-base\")\n","pd.DataFrame(fillmask(\"The cat is so <mask> .\"))"],"execution_count":15,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>sequence</th>\n","      <th>score</th>\n","      <th>token</th>\n","      <th>token_str</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>The cat is so cute.</td>\n","      <td>0.191843</td>\n","      <td>11962</td>\n","      <td>cute</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>The cat is so sweet.</td>\n","      <td>0.051524</td>\n","      <td>4045</td>\n","      <td>sweet</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>The cat is so funny.</td>\n","      <td>0.033595</td>\n","      <td>6269</td>\n","      <td>funny</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>The cat is so handsome.</td>\n","      <td>0.032893</td>\n","      <td>19222</td>\n","      <td>handsome</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>The cat is so beautiful.</td>\n","      <td>0.032314</td>\n","      <td>2721</td>\n","      <td>beautiful</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                   sequence     score  token   token_str\n","0       The cat is so cute.  0.191843  11962        cute\n","1      The cat is so sweet.  0.051524   4045       sweet\n","2      The cat is so funny.  0.033595   6269       funny\n","3   The cat is so handsome.  0.032893  19222    handsome\n","4  The cat is so beautiful.  0.032314   2721   beautiful"]},"metadata":{"tags":[]},"execution_count":15}]},{"cell_type":"code","metadata":{"id":"bgLnGwIUh7lH","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1618945587017,"user_tz":-180,"elapsed":7177,"user":{"displayName":"Savas Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}},"outputId":"3ee58ff6-93d4-4304-f56c-2aa7dd15c45d"},"source":["tokenizer = AlbertTokenizer.from_pretrained('albert-base-v2')\n","print(tokenizer.mask_token)\n","tokenizer = RobertaTokenizer.from_pretrained('roberta-base')\n","print(tokenizer.mask_token)"],"execution_count":16,"outputs":[{"output_type":"stream","text":["[MASK]\n","<mask>\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"vJSX_CBFh7lI"},"source":[""],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"9VENpwqvh7lI","colab":{"base_uri":"https://localhost:8080/","height":449,"referenced_widgets":["c4ad9c4a4e4c40bb86e1bdc988ee17dc","fd408398c9e04cb79512ae6b535cb3e8","4a58acc8943d4c3895c4d4f46c4a4fac","0f29da9a53264c4ab198e404cfad04b3","57c469cf679a41a08e2e97509f435f69","75acbb2201ab42d38086a89d6130049d","c3a7283825e3432e90d556c2034e6491","c2a34c719ae1431d9a2a2ad3f9dd0c3b","437c5aeb7d684138ad59560b8ed7ed56","e716d29b444748f6be532532a94118db","db6f33e89efd4651b68678b5f80430d2","66852982ce004612827b6045bbb08019","82c842703f7a4460bfd2b1436bcbb4db","3f61a882c48246dfa2e61c8bfb253f3b","f69758cb102243479d2100499b489f7d","50fd087844b34a71b4d0bcb61404493c","3adcee66d5a94187a205656ed519e5ef","eb104d3ce4684e64af83c4522e857858","ef9318a9839b4131bbc8c20229a3f367","42f30c33bf434344bcb637680558846c","30bc0d0f8a7e4cd48111cf56d684ea1e","555bb4174a0442a4b801ab80dd7a6e37","6f9275557b154f89b27f1b27a74475cd","c036c60de37b4bd584c091817e6b9eb5","e4637b4bab3b4ee68ad5e08279b17499","88406bd4e5b748c391e42dff6fe4ddc2","1e319dcd49cf48ecbfb2b1907ba7df46","bc647f746ad54cdd8c57efc96896dacd","15bf454a31a64c1fb57a7790daba9660","446b6eed334f4491a1cb062cd4507e79","fcd01513fda0460fa82414a25ab6e640","78bb75f6b3f4424297a0e1eac91160ab","534d9ff20a91407596bd0e741e69bebf","35fae51bc27542eab50849ab549f2da5","66ce3c0c875246e086ecea89fd7449c5","e70447c7499c499fad5a1ce3ac29957b","9172fcc8bbfb4f2eba2dc23b6f4aa88a","6e0d79aacbce43a183df1a672d50d69b","d7824ef9431e4d2faa7aa81e24a8ecf4","83ff5c23fafa4c0498cbe7217891255c"]},"executionInfo":{"status":"ok","timestamp":1618945612722,"user_tz":-180,"elapsed":15286,"user":{"displayName":"Savas Yıldırım","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhdhYZMfq-hvK2xI7HqkzvJuCbfgFrIs4wypQEm5w=s64","userId":"10717726124681851716"}},"outputId":"90b8b683-9446-4d2b-a0c4-ba7bd91606f4"},"source":["from transformers import pipeline\n","fillmask = pipeline(\"fill-mask\", model=\"google/electra-small-generator\")\n","q=fillmask(f\"The cat is very {fillmask.tokenizer.mask_token} .\")\n","pd.DataFrame(q)"],"execution_count":17,"outputs":[{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"c4ad9c4a4e4c40bb86e1bdc988ee17dc","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=463.0, style=ProgressStyle(description_…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"437c5aeb7d684138ad59560b8ed7ed56","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=54236116.0, style=ProgressStyle(descrip…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"3adcee66d5a94187a205656ed519e5ef","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=231508.0, style=ProgressStyle(descripti…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"e4637b4bab3b4ee68ad5e08279b17499","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=466062.0, style=ProgressStyle(descripti…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"display_data","data":{"application/vnd.jupyter.widget-view+json":{"model_id":"534d9ff20a91407596bd0e741e69bebf","version_minor":0,"version_major":2},"text/plain":["HBox(children=(FloatProgress(value=0.0, description='Downloading', max=29.0, style=ProgressStyle(description_w…"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>sequence</th>\n","      <th>score</th>\n","      <th>token</th>\n","      <th>token_str</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>the cat is very friendly.</td>\n","      <td>0.098157</td>\n","      <td>5379</td>\n","      <td>friendly</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>the cat is very cute.</td>\n","      <td>0.086665</td>\n","      <td>10140</td>\n","      <td>cute</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>the cat is very sensitive.</td>\n","      <td>0.054568</td>\n","      <td>7591</td>\n","      <td>sensitive</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>the cat is very shy.</td>\n","      <td>0.033855</td>\n","      <td>11004</td>\n","      <td>shy</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>the cat is very smart.</td>\n","      <td>0.031776</td>\n","      <td>6047</td>\n","      <td>smart</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                     sequence     score  token  token_str\n","0   the cat is very friendly.  0.098157   5379   friendly\n","1       the cat is very cute.  0.086665  10140       cute\n","2  the cat is very sensitive.  0.054568   7591  sensitive\n","3        the cat is very shy.  0.033855  11004        shy\n","4      the cat is very smart.  0.031776   6047      smart"]},"metadata":{"tags":[]},"execution_count":17}]},{"cell_type":"code","metadata":{"id":"toIsEyewh7lJ"},"source":[""],"execution_count":null,"outputs":[]}]}
